Metric details with threshold from accuracy metric
score
threshold
logloss
0.454124
nan
auc
0.858947
nan
f1
0.825033
0.310846
accuracy
0.792628
0.310846
precision
0.771592
0.310846
recall
0.886429
0.310846
mcc
0.581852
0.310846
Confusion matrix (at threshold=0.310846)
Predicted as long
Predicted as short
Labeled as long
1343
640
Labeled as short
277
2162
Learning curves
Decision Tree
Tree #1
Rules
if (Total Costs <= 8584.205) and (Total Costs <= 4865.995) and (CCS Diagnosis Code <= 253.5) then class: short (proba: 95.64%) | based on 3,278 samples
if (Total Costs <= 8584.205) and (Total Costs > 4865.995) and (CCS Diagnosis Code <= 454.5) then class: short (proba: 72.63%) | based on 2,769 samples
if (Total Costs > 8584.205) and (APR Severity of Illness Code <= 2.5) and (APR Medical Surgical Description > 0.5) then class: short (proba: 57.49%) | based on 1,868 samples
if (Total Costs > 8584.205) and (APR Severity of Illness Code <= 2.5) and (APR Medical Surgical Description <= 0.5) then class: long (proba: 75.53%) | based on 1,847 samples
if (Total Costs > 8584.205) and (APR Severity of Illness Code > 2.5) and (Total Costs > 15573.525) then class: long (proba: 95.33%) | based on 1,797 samples
if (Total Costs > 8584.205) and (APR Severity of Illness Code > 2.5) and (Total Costs <= 15573.525) then class: long (proba: 78.08%) | based on 958 samples
if (Total Costs <= 8584.205) and (Total Costs <= 4865.995) and (CCS Diagnosis Code > 253.5) then class: short (proba: 68.65%) | based on 453 samples
if (Total Costs <= 8584.205) and (Total Costs > 4865.995) and (CCS Diagnosis Code > 454.5) then class: long (proba: 86.44%) | based on 295 samples